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A General Formulation for Redundant Integration of Finite Differences and Phase Unwrapping on a Sparse Multidimensional Domain

机译:稀疏多维域上有限差分和相位展开的冗余积分的通用公式

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摘要

Phase unwrapping and integration of finite differences are key problems in several technical fields, among which is synthetic aperture radar (SAR) interferometry. In this paper, we propose a general formulation for robust and efficient integration of finite differences and for phase unwrapping, which includes standard techniques (e.g., minimum cost flow and least squares phase unwrapping) as subcases. The proposed approach allows obtaining more reliable and accurate solutions by exploiting redundant differential estimates (not only between nearest neighboring points) and multidimensional information (e.g., multitemporal). In addition, a model of the signal (e.g., multibaseline or multifrequency) or external data (e.g., GPS or leveling measurements) can be integrated. The method requires the solution of linear or quadratic programming problems, for which computationally efficient algorithms exist. The validation tests performed on real and simulated SAR data confirm the validity of the method, which was integrated in our production chain and successfully used also in massive productions.
机译:相位展开和有限差分的积分是几个技术领域的关键问题,其中包括合成孔径雷达(SAR)干涉测量法。在本文中,我们为有限差分的稳健和有效集成以及相位展开提出了一种通用公式,其中包括一些标准技术(例如最小成本流和最小平方相位展开)作为子案例。所提出的方法允许通过利用冗余差分估计(不仅在最近的相邻点之间)和多维信息(例如,多时间的)来获得更可靠和准确的解决方案。另外,可以集成信号(例如,多基线或多频率)或外部数据(例如,GPS或水平测量)的模型。该方法需要解决线性或二次规划问题,对于这些问题存在计算上高效的算法。对真实和模拟SAR数据进行的验证测试证实了该方法的有效性,该方法已集成到我们的生产链中,并已成功用于大规模生产。

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